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Merge pull request #296779 from Padmalathas/FreshnessReviewPass-Batch1
Updating the metadata for ms.date - FreshnessPass
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articles/batch/batch-job-schedule.md

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title: Schedule Batch jobs for efficiency
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description: Learn how to schedule Batch jobs to manage your tasks, prioritize jobs to run first, and minimize resource usage.
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ms.topic: how-to
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ms.date: 06/13/2024
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ms.date: 03/21/2025
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---
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# Schedule Batch jobs for efficiency

articles/batch/jobs-and-tasks.md

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title: Jobs and tasks in Azure Batch
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description: Learn about jobs and tasks and how they are used in an Azure Batch workflow from a development standpoint.
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ms.topic: conceptual
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ms.date: 06/13/2024
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ms.date: 03/21/2025
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---
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# Jobs and tasks in Azure Batch
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articles/batch/nodes-and-pools.md

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title: Nodes and pools in Azure Batch
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description: Learn about compute nodes and pools and how they are used in an Azure Batch workflow from a development standpoint.
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ms.topic: conceptual
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ms.date: 08/08/2024
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ms.date: 03/21/2025
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# Nodes and pools in Azure Batch
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articles/batch/quick-run-python.md

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---
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title: 'Quickstart: Use Python to create a pool and run a job'
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description: Follow this quickstart to run an app that uses the Azure Batch client library for Python to create and run Batch pools, nodes, jobs, and tasks.
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ms.date: 03/01/2024
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ms.date: 03/21/2025
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ms.topic: quickstart
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ms.devlang: python
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ms.custom: mvc, devx-track-python, mode-api
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> [!div class="checklist"]
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> - Uploads several input data files to an Azure Storage blob container to use for Batch task processing.
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> - Creates a pool of two virtual machines (VMs), or compute nodes, running Ubuntu 20.04 LTS OS.
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> - Creates a pool of two virtual machines (VMs), or compute nodes, running Ubuntu 22.04 LTS OS.
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> - Creates a job and three tasks to run on the nodes. Each task processes one of the input files by using a Bash shell command line.
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> - Displays the output files that the tasks return.
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### Create a pool of compute nodes
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To create a Batch pool, the app uses the [PoolAddParameter](/python/api/azure-batch/azure.batch.models.pooladdparameter) class to set the number of nodes, VM size, and pool configuration. The following [VirtualMachineConfiguration](/python/api/azure-batch/azure.batch.models.virtualmachineconfiguration) object specifies an [ImageReference](/python/api/azure-batch/azure.batch.models.imagereference) to an Ubuntu Server 20.04 LTS Azure Marketplace image. Batch supports a wide range of Linux and Windows Server Marketplace images, and also supports custom VM images.
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To create a Batch pool, the app uses the [PoolAddParameter](/python/api/azure-batch/azure.batch.models.pooladdparameter) class to set the number of nodes, VM size, and pool configuration. The following [VirtualMachineConfiguration](/python/api/azure-batch/azure.batch.models.virtualmachineconfiguration) object specifies an [ImageReference](/python/api/azure-batch/azure.batch.models.imagereference) to an Ubuntu Server 22.04 LTS Azure Marketplace image. Batch supports a wide range of Linux and Windows Server Marketplace images, and also supports custom VM images.
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The `POOL_NODE_COUNT` and `POOL_VM_SIZE` are defined constants. The app creates a pool of two size Standard_DS1_v2 nodes. This size offers a good balance of performance versus cost for this quickstart.
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image_reference=batchmodels.ImageReference(
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publisher="canonical",
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offer="0001-com-ubuntu-server-focal",
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sku="20_04-lts",
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sku="22_04-lts",
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version="latest"
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),
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node_agent_sku_id="batch.node.ubuntu 20.04"),
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node_agent_sku_id="batch.node.ubuntu 22.04"),
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vm_size=config.POOL_VM_SIZE,
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target_dedicated_nodes=config.POOL_NODE_COUNT
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)

articles/batch/tutorial-run-python-batch-azure-data-factory.md

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description: Learn how to use Batch Explorer, Azure Storage Explorer, and a Python script to run a Batch workload through an Azure Data Factory pipeline.
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ms.devlang: python
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ms.topic: tutorial
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ms.date: 12/23/2024
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ms.date: 03/21/2025
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ai-usage: ai-assisted
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ms.custom: mvc, devx-track-python
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---

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